Mathematics of Operations Research
Lectures on modern convex optimization: analysis, algorithms, and engineering applications
Lectures on modern convex optimization: analysis, algorithms, and engineering applications
Robust Solutions to Uncertain Semidefinite Programs
SIAM Journal on Optimization
Operations Research
Adjustable robust solutions of uncertain linear programs
Mathematical Programming: Series A and B
Uncertain convex programs: randomized solutions and confidence levels
Mathematical Programming: Series A and B
Ambiguous chance constrained problems and robust optimization
Mathematical Programming: Series A and B
Convex Approximations of Chance Constrained Programs
SIAM Journal on Optimization
A Sample Approximation Approach for Optimization with Probabilistic Constraints
SIAM Journal on Optimization
A Robust Optimization Perspective on Stochastic Programming
Operations Research
Operations Research
Constructing Risk Measures from Uncertainty Sets
Operations Research
Constructing Uncertainty Sets for Robust Linear Optimization
Operations Research
Robust solutions of uncertain linear programs
Operations Research Letters
Robust linear optimization under general norms
Operations Research Letters
Constructing Uncertainty Sets for Robust Linear Optimization
Operations Research
Asset allocation using reliability method
Mathematical and Computer Modelling: An International Journal
Multiple Objectives Satisficing Under Uncertainty
Operations Research
Safe Approximations of Ambiguous Chance Constraints Using Historical Data
INFORMS Journal on Computing
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We review and develop different tractable approximations to individual chance-constrained problems in robust optimization on a variety of uncertainty sets and show their interesting connections with bounds on the conditional-value-at-risk (CVaR) measure. We extend the idea to joint chance-constrained problems and provide a new formulation that improves upon the standard approach. Our approach builds on a classical worst-case bound for order statistics problems and is applicable even if the constraints are correlated. We provide an application of the model on a network resource allocation problem with uncertain demand.